Data Mining Benno Stein
Contents I. Introduction
Objectives
Related Fields 1. Statistics
Literature Data Mining:
Software Programming:
Chapter DM:I I. Introduction
Data Mining Overview Definition 1 (Knowledge Discovery in Databases, KDD [Fayyad 1996, Wrobel 1998])
Data Mining Overview Definition 1 (Knowledge Discovery in Databases, KDD [Fayyad 1996, Wrobel 1998])
Remarks:
Data Mining Overview
Data Mining Overview
Data Mining Overview
Retrieval
Remarks:
Data Mining Overview Relevant Data Mining Methods
Chapter DM:I
On Data [Tan et al. 2005]
On Data [Tan et al. 2005]
On Data [Tan et al. 2005]
On Data [Tan et al. 2005]
On Data [Tan et al. 2005]
On Data [Tan et al. 2005] Types of Attributes
On Data [Tan et al. 2005] Types of Attributes
On Data [Tan et al. 2005] Types of Attributes
On Data [Tan et al. 2005] Types of Attributes
On Data [Tan et al. 2005] Types of Attributes
On Data [Tan et al. 2005] Types of Attributes
On Data [Tan et al. 2005] Types of Attributes
On Data [Tan et al. 2005] Types of Attributes
Remarks:
On Data [Tan et al. 2005] Types of Data Sets
On Data [Tan et al. 2005] Types of Data Sets
On Data [Tan et al. 2005] Types of Data Sets: Record Data
On Data [Tan et al. 2005] Types of Data Sets: Graph Data
On Data [Tan et al. 2005] Types of Data Sets: Ordered Data
On Data [Tan et al. 2005] Data Quality
On Data [Tan et al. 2005] Data Quality
On Data [Tan et al. 2005] Data Quality
On Data [Tan et al. 2005] Data Quality: Noise
On Data [Tan et al. 2005] Data Quality: Outliers
On Data [Tan et al. 2005] Data Quality: Outliers
On Data [Tan et al. 2005] Data Quality: Missing Values
On Data [Tan et al. 2005] Data Preprocessing
Chapter DM:II II. Cluster Analysis
Cluster Analysis Basics Cluster analysis is the unsupervised classification of a set of objects in groups,
Cluster Analysis Basics Cluster analysis is the unsupervised classification of a set of objects in groups,
Remarks:
Cluster Analysis Basics Let x1, . . . xn denote the p-dimensional feature vectors of n objects:
Cluster Analysis Basics Let x1, . . . xn denote the p-dimensional feature vectors of n objects:
Cluster Analysis Basics Let x1, . . . xn denote the p-dimensional feature vectors of n objects:
Cluster Analysis Basics Definition 3 (Exclusive Clustering [splitting])
Cluster Analysis Basics Definition 3 (Exclusive Clustering [splitting])
Cluster Analysis Basics Definition 3 (Exclusive Clustering [splitting])
Cluster Analysis Basics Main Stages of a Cluster Analysis
Cluster Analysis Basics Feature Extraction and Preprocessing [cluster analysis stages]
Cluster Analysis Basics Feature Extraction and Preprocessing [cluster analysis stages]
Cluster Analysis Basics Computation of Distances or Similarities [cluster analysis stages]
Remarks:
Cluster Analysis Basics Computation of Distances or Similarities
Cluster Analysis Basics Computation of Distances or Similarities
Cluster Analysis Basics Computation of Distances or Similarities
Cluster Analysis Basics Computation of Distances or Similarities
Remarks:
Cluster Analysis Basics Merging Principles [cluster analysis stages]
Chapter DM:II
Hierarchical Cluster Analysis Merging Principles
Hierarchical Cluster Analysis Hierarchical Agglomerative Algorithm
Hierarchical Cluster Analysis Hierarchical Agglomerative Algorithm
Hierarchical Cluster Analysis Single Link: Cluster Distance Measure dC = Nearest Neighbor
Hierarchical Cluster Analysis Single Link: Cluster Distance Measure dC = Nearest Neighbor
Hierarchical Cluster Analysis Single Link: Cluster Distance Measure dC = Nearest Neighbor
Hierarchical Cluster Analysis Single Link: Cluster Distance Measure dC = Nearest Neighbor
Hierarchical Cluster Analysis Single Link: Cluster Distance Measure dC = Nearest Neighbor
Hierarchical Cluster Analysis Single Link: Cluster Distance Measure dC = Nearest Neighbor
Hierarchical Cluster Analysis Single Link: Cluster Distance Measure dC = Nearest Neighbor
Hierarchical Cluster Analysis Single Link: Cluster Distance Measure dC = Nearest Neighbor
Hierarchical Cluster Analysis Single Link: Cluster Distance Measure dC = Nearest Neighbor
Hierarchical Cluster Analysis Distance Re-Computation after each Merging Step [algorithm]
Hierarchical Cluster Analysis Distance Re-Computation after each Merging Step [algorithm]
Hierarchical Cluster Analysis Distance Re-Computation after each Merging Step [algorithm]
Hierarchical Cluster Analysis Distance Re-Computation after each Merging Step [algorithm]
Hierarchical Cluster Analysis Distance Measures of Hierarchical Agglomerative Algorithms [characteristics]
Hierarchical Cluster Analysis Ward Criterion
Hierarchical Cluster Analysis Ward Criterion
Hierarchical Cluster Analysis Ward Criterion
Hierarchical Cluster Analysis Ward Criterion
Hierarchical Cluster Analysis Ward Criterion
Hierarchical Cluster Analysis Ward Criterion
Hierarchical Cluster Analysis Ward Criterion
Hierarchical Cluster Analysis Update Formula for Cluster Distances
Hierarchical Cluster Analysis Update Formula for Cluster Distances
Hierarchical Cluster Analysis Update Formula for Cluster Distances
Hierarchical Cluster Analysis Update Formula for Cluster Distances
Hierarchical Cluster Analysis Update Formula for Cluster Distances
Remarks:
Hierarchical Cluster Analysis Chaining Problem of Single Link (dC = Nearest Neighbor)
Hierarchical Cluster Analysis Chaining Problem of Single Link (dC = Nearest Neighbor)
Hierarchical Cluster Analysis Chaining Problem of Single Link (dC = Nearest Neighbor)
Hierarchical Cluster Analysis Chaining Problem of Single Link (dC = Nearest Neighbor)
Hierarchical Cluster Analysis Chaining Problem of Single Link (dC = Nearest Neighbor)
Hierarchical Cluster Analysis Chaining Problem of Single Link (dC = Nearest Neighbor) [characteristics]
Hierarchical Cluster Analysis Chaining Problem of Single Link (dC = Nearest Neighbor)
Hierarchical Cluster Analysis Chaining Problem of Single Link (dC = Nearest Neighbor)
Hierarchical Cluster Analysis Chaining Problem of Single Link (dC = Nearest Neighbor)
Hierarchical Cluster Analysis Chaining Problem of Single Link (dC = Nearest Neighbor)
Remarks:
Hierarchical Cluster Analysis Chaining Problem of Single Link (dC = k-Nearest-Neighbor)
Hierarchical Cluster Analysis Chaining Problem of Single Link (dC = k-Nearest-Neighbor)
Hierarchical Cluster Analysis Chaining Problem of Single Link (dC = k-Nearest-Neighbor)
Hierarchical Cluster Analysis Chaining Problem of Single Link (dC = k-Nearest-Neighbor)
Hierarchical Cluster Analysis Chaining Problem of Single Link (dC = k-Nearest-Neighbor)
Hierarchical Cluster Analysis Chaining Problem of Single Link (dC = k-Nearest-Neighbor)
Hierarchical Cluster Analysis Chaining Problem of Single Link (dC = k-Nearest-Neighbor)
Hierarchical Cluster Analysis Chaining Problem of Single Link (dC = k-Nearest-Neighbor)
Hierarchical Cluster Analysis Chaining Problem of Single Link (dC = k-Nearest-Neighbor)
Hierarchical Cluster Analysis Chaining Problem of Single Link (dC = k-Nearest-Neighbor)
Hierarchical Cluster Analysis Chaining Problem of Single Link (dC = k-Nearest-Neighbor)
Hierarchical Cluster Analysis Nesting Problem of Complete Link (dC = Furthest Neighbor)
Hierarchical Cluster Analysis Nesting Problem of Complete Link (dC = Furthest Neighbor)
Hierarchical Cluster Analysis Nesting Problem of Complete Link (dC = Furthest Neighbor) [characteristics]
Hierarchical Cluster Analysis Nesting Problem of Complete Link (dC = Furthest Neighbor)
Hierarchical Cluster Analysis Nesting Problem of Complete Link (dC = Furthest Neighbor)
Hierarchical Cluster Analysis Nesting Problem of Complete Link (dC = Furthest Neighbor) [characteristics]
Hierarchical Cluster Analysis Nesting Problem of Complete Link (dC = Furthest Neighbor)
Hierarchical Cluster Analysis Nesting Problem of Complete Link (dC = Furthest Neighbor)
Hierarchical Cluster Analysis Characteristics of Hierarchical Agglomerative Algorithms [distance measures]
Hierarchical Cluster Analysis Characteristics of Hierarchical Agglomerative Algorithms [distance measures]
Hierarchical Cluster Analysis Characteristics of Hierarchical Agglomerative Algorithms [distance measures]
Remarks:
Hierarchical Cluster Analysis Merging Principles
Hierarchical Cluster Analysis Hierarchical Divisive Algorithm
Hierarchical Cluster Analysis Hierarchical Divisive Algorithm
Remarks:
Hierarchical Cluster Analysis MinCut
Hierarchical Cluster Analysis MinCut
Hierarchical Cluster Analysis MinCut
Hierarchical Cluster Analysis MinCut
Hierarchical Cluster Analysis MinCut
Hierarchical Cluster Analysis MinCut
Hierarchical Cluster Analysis MinCut
Remarks:
Hierarchical Cluster Analysis Splitting Problem of MinCut
Hierarchical Cluster Analysis Splitting Problem of MinCut
Hierarchical Cluster Analysis Splitting Problem of MinCut
Hierarchical Cluster Analysis Splitting Problem of MinCut
Hierarchical Cluster Analysis Splitting Problem of MinCut
Hierarchical Cluster Analysis Splitting Problem of MinCut
Hierarchical Cluster Analysis Splitting Problem of MinCut
Hierarchical Cluster Analysis Splitting Problem of MinCut
Remarks:
Hierarchical Cluster Analysis Combination of Hierarchical Algorithms
Hierarchical Cluster Analysis Combination of Hierarchical Algorithms
Hierarchical Cluster Analysis Combination of Hierarchical Algorithms
Chapter DM:II
Iterative Cluster Analysis Merging Principles
Iterative Cluster Analysis Exemplar-Based Algorithm
Iterative Cluster Analysis Exemplar-Based Algorithm
Remarks:
Iterative Cluster Analysis k-Means with Minimization Criterion e = Variance
Iterative Cluster Analysis k-Means with Minimization Criterion e = Variance
Iterative Cluster Analysis k-Means with Minimization Criterion e = Variance
Iterative Cluster Analysis k-Means with Minimization Criterion e = Variance
Iterative Cluster Analysis k-Means with Minimization Criterion e = Variance
Iterative Cluster Analysis k-Means with Minimization Criterion e = Variance
Iterative Cluster Analysis k-Means with Minimization Criterion e = Variance
Iterative Cluster Analysis k-Means with Minimization Criterion e = Variance
Iterative Cluster Analysis Minimization Criteria of Exemplar-Based Algorithms [algorithm]
Remarks:
Remarks: (continued)
Iterative Cluster Analysis k-Means versus Single Link
Iterative Cluster Analysis k-Means versus Single Link
Iterative Cluster Analysis k-Means versus Single Link
Iterative Cluster Analysis k-Means versus Single Link
Iterative Cluster Analysis k-Means versus Single Link
Iterative Cluster Analysis k-Means versus Single Link
Iterative Cluster Analysis Exclusive versus Non-Exclusive Algorithms
Iterative Cluster Analysis Exclusive versus Non-Exclusive Algorithms
Iterative Cluster Analysis Exclusive versus Non-Exclusive Algorithms
Remarks: The domain of the linguistic variable of the Fuzzy model is comprised of k elements, which
Chapter DM:II
Density-Based Cluster Analysis Merging Principles
Density-Based Cluster Analysis Density-based algorithms strive to partition the graph G = hV, E, wi, better: the set
Density-Based Cluster Analysis Density-based algorithms strive to partition the graph G = hV, E, wi, better: the set
Density-Based Cluster Analysis Density Estimation with Gaussian Kernel for the Example
Density-Based Cluster Analysis Density Estimation with Gaussian Kernel for the Example
Density-Based Cluster Analysis Density Estimation with Gaussian Kernel for the Example
Density-Based Cluster Analysis Density Estimation with Gaussian Kernel for the Example
Remarks:
Density-Based Cluster Analysis DBSCAN: Density Estimation Principle [Ester et al. 1996]
Density-Based Cluster Analysis DBSCAN: Density Estimation Principle
Density-Based Cluster Analysis DBSCAN: Cluster Interpretation
Density-Based Cluster Analysis DBSCAN: Cluster Interpretation
Remarks:
Density-Based Cluster Analysis DBSCAN: Algorithm
Density-Based Cluster Analysis DBSCAN: Algorithm
Density-Based Cluster Analysis DBSCAN
Density-Based Cluster Analysis DBSCAN
Density-Based Cluster Analysis DBSCAN
Density-Based Cluster Analysis DBSCAN
Density-Based Cluster Analysis DBSCAN
Density-Based Cluster Analysis DBSCAN
Density-Based Cluster Analysis DBSCAN
Density-Based Cluster Analysis DBSCAN
Density-Based Cluster Analysis DBSCAN
Density-Based Cluster Analysis DBSCAN
Remarks:
Density-Based Cluster Analysis Merging Principles
Density-Based Cluster Analysis MajorClust: Density Estimation Principle [Stein/Niggemann 1999]
Density-Based Cluster Analysis MajorClust: Density Estimation Principle [Stein/Niggemann 1999]
Density-Based Cluster Analysis MajorClust: Density Estimation Principle [Stein/Niggemann 1999]
Density-Based Cluster Analysis MajorClust: Algorithm
Density-Based Cluster Analysis MajorClust: Algorithm
Density-Based Cluster Analysis MajorClust
Density-Based Cluster Analysis MajorClust
Density-Based Cluster Analysis MajorClust
Density-Based Cluster Analysis MajorClust
Density-Based Cluster Analysis MajorClust
Density-Based Cluster Analysis MajorClust
Density-Based Cluster Analysis MajorClust
Density-Based Cluster Analysis MajorClust
Density-Based Cluster Analysis MajorClust
Density-Based Cluster Analysis MajorClust
Density-Based Cluster Analysis MajorClust
Density-Based Cluster Analysis MajorClust
Remarks:
Density-Based Cluster Analysis MajorClust: Density Estimation Principle
Density-Based Cluster Analysis MajorClust: Density Estimation Principle
Density-Based Cluster Analysis MajorClust: Density Estimation Principle
Density-Based Cluster Analysis MajorClust: Density Estimation Principle
Density-Based Cluster Analysis MajorClust: Density Estimation Principle
Density-Based Cluster Analysis MajorClust: Density Estimation Principle
Density-Based Cluster Analysis DBSCAN versus MajorClust: Low-Dimensional Data
Density-Based Cluster Analysis DBSCAN versus MajorClust: Low-Dimensional Data
Density-Based Cluster Analysis DBSCAN versus MajorClust: Low-Dimensional Data
Density-Based Cluster Analysis DBSCAN versus MajorClust: Low-Dimensional Data
Density-Based Cluster Analysis DBSCAN versus MajorClust: Low-Dimensional Data
Remarks:
Density-Based Cluster Analysis DBSCAN versus MajorClust: High-Dimensional Data
Density-Based Cluster Analysis DBSCAN versus MajorClust: High-Dimensional Data
Remarks:
Chapter DM:II
Cluster Evaluation Overview
Cluster Evaluation [Tan/Steinbach/Kumar 2005]
Cluster Evaluation [Tan/Steinbach/Kumar 2005]
Cluster Evaluation [Tan/Steinbach/Kumar 2005]
Cluster Evaluation [Tan/Steinbach/Kumar 2005]
Cluster Evaluation Overview
Cluster Evaluation Overview
Cluster Evaluation Overview
Cluster Evaluation (1) External Validity Measures: F -Measure (for a Target Class)
Cluster Evaluation (1) External Validity Measures: F -Measure (for a Target Class)
Cluster Evaluation (1) External Validity Measures: F -Measure (for a Target Class)
Cluster Evaluation (1) External Validity Measures: F -Measure (for a Target Class)
Cluster Evaluation (1) External Validity Measures: F -Measure (for a Target Class)
Cluster Evaluation (1) External Validity Measures: F -Measure (for a Target Class)
Cluster Evaluation (1) External Validity Measures: F -Measure (for a Target Class)
Cluster Evaluation (1) External Validity Measures: F -Measure (for a Target Class)
Cluster Evaluation (1) External Validity Measures: F -Measure (for a Target Class)
Cluster Evaluation (1) External Validity Measures: F -Measure (for a Target Class)
Cluster Evaluation (1) External Validity Measures: F -Measure (for a Target Class)
Cluster Evaluation (1) External Validity Measures: F -Measure (for a Target Class)
Cluster Evaluation (1) External Validity Measures: F -Measure (for a Target Class)
Cluster Evaluation (1) External Validity Measures: F -Measure (for a Target Class)
Cluster Evaluation (1) External Validity Measures: F -Measure (for a Clustering)
Cluster Evaluation (1) External Validity Measures: F -Measure (for a Clustering)
Cluster Evaluation (1) External Validity Measures: F -Measure (for a Clustering)
Remarks:
Cluster Evaluation (1) External Validity Measures: Entropy
Cluster Evaluation (1) External Validity Measures: Entropy
Cluster Evaluation (1) External Validity Measures: Entropy
Cluster Evaluation (1) External Validity Measures: Entropy
Cluster Evaluation (1) External Validity Measures: Entropy
Cluster Evaluation (1) External Validity Measures: Rand, Jaccard
Cluster Evaluation (1) External Validity Measures: Rand, Jaccard
Cluster Evaluation (2) Internal Validity Measures: Edge Correlation [Tan/Steinbach/Kumar 2005]
Cluster Evaluation (2) Internal Validity Measures: Edge Correlation [Tan/Steinbach/Kumar 2005]
Cluster Evaluation (2) Internal Validity Measures: Edge Correlation [Tan/Steinbach/Kumar 2005]
Cluster Evaluation (2) Internal Validity Measures: Edge Correlation [Tan/Steinbach/Kumar 2005]
Cluster Evaluation (2) Internal Validity Measures: Edge Correlation [Tan/Steinbach/Kumar 2005]
Cluster Evaluation (2) Internal Validity Measures: Edge Correlation [Tan/Steinbach/Kumar 2005]
Cluster Evaluation (2) Internal Validity Measures: Edge Correlation [Tan/Steinbach/Kumar 2005]
Cluster Evaluation (2) Internal Validity Measures: Edge Correlation [Tan/Steinbach/Kumar 2005]
Cluster Evaluation (2) Internal Validity Measures: Edge Correlation [Tan/Steinbach/Kumar 2005]
Cluster Evaluation (2) Internal Validity Measures: Edge Correlation [Tan/Steinbach/Kumar 2005]
Cluster Evaluation (2) Internal Validity Measures: Structural Analysis
Cluster Evaluation (2) Internal Validity Measures: Structural Analysis
Cluster Evaluation (2) Internal Validity Measures: Structural Analysis
Cluster Evaluation (2) Internal Validity Measures: Structural Analysis
Cluster Evaluation (2) Internal Validity Measures: Dunn Index
Cluster Evaluation (2) Internal Validity Measures: Dunn Index
Cluster Evaluation (2) Internal Validity Measures: Dunn Index
Cluster Evaluation (2) Internal Validity Measures: Dunn Index
Cluster Evaluation (2) Internal Validity Measures: Dunn Index
Cluster Evaluation (2) Internal Validity Measures: Expected Density ρ
Cluster Evaluation (2) Internal Validity Measures: Expected Density ρ
Cluster Evaluation (2) Internal Validity Measures: Expected Density ρ
Cluster Evaluation (2) Internal Validity Measures: Expected Density ρ
Cluster Evaluation (2) Internal Validity Measures: Expected Density ρ
Cluster Evaluation (2) Internal Validity Measures: Expected Density ρ
Cluster Evaluation (2) Internal Validity Measures: Expected Density ρ
Cluster Evaluation (2) Internal Validity Measures: Expected Density ρ
Cluster Evaluation (2) Internal Validity Measures: Expected Density ρ
Cluster Evaluation (3) Relative Validity Measures: Elbow Criterion
Cluster Evaluation (3) Relative Validity Measures: Elbow Criterion
Cluster Evaluation (3) Relative Validity Measures: Elbow Criterion
Cluster Evaluation (3) Relative Validity Measures: Elbow Criterion
Cluster Evaluation (3) Relative Validity Measures: Elbow Criterion
Cluster Evaluation (3) Relative Validity Measures: Elbow Criterion
Cluster Evaluation Correlation between External and Internal Measures
Cluster Evaluation Correlation between External and Internal Measures
Cluster Evaluation Correlation between External and Internal Measures
Cluster Evaluation Correlation between External and Internal Measures
Cluster Evaluation Correlation between External and Internal Measures
Cluster Evaluation Correlation between External and Internal Measures
Chapter DM:II
Constrained Cluster Analysis Person Resolution Task
Constrained Cluster Analysis Person Resolution Task
Constrained Cluster Analysis Person Resolution Task
Constrained Cluster Analysis Person Resolution Task
Constrained Cluster Analysis Person Resolution Task
Constrained Cluster Analysis Person Resolution Task
Constrained Cluster Analysis # Referents
Constrained Cluster Analysis Applied to Multi-Document Resolution
Constrained Cluster Analysis Applied to Multi-Document Resolution
Constrained Cluster Analysis Applied to Multi-Document Resolution
Constrained Cluster Analysis Applied to Multi-Document Resolution
Constrained Cluster Analysis Applied to Multi-Document Resolution
Constrained Cluster Analysis Applied to Multi-Document Resolution
Constrained Cluster Analysis Idealized Class Membership Distribution over Similarities
Constrained Cluster Analysis Membership Distribution under tf·idf Vector Space Model
Constrained Cluster Analysis Membership Distribution under Context-Based Vector Space Model
Constrained Cluster Analysis Membership Distribution under Ontology Alignment Model
Constrained Cluster Analysis In-Depth: Multi-Class Hierarchical Classification
Constrained Cluster Analysis In-Depth: Multi-Class Hierarchical Classification
Constrained Cluster Analysis In-Depth: Multi-Class Hierarchical Classification
Constrained Cluster Analysis Membership Distribution under Optimized Retrieval Model Combination
Constrained Cluster Analysis Membership Distribution under Optimized Retrieval Model Combination
Constrained Cluster Analysis Membership Distribution under Optimized Retrieval Model Combination
Constrained Cluster Analysis Membership Distribution under Optimized Retrieval Model Combination
Constrained Cluster Analysis Membership Distribution under Optimized Retrieval Model Combination
Constrained Cluster Analysis In-Depth: Analysis of Classifier Effectiveness
Constrained Cluster Analysis In-Depth: Analysis of Classifier Effectiveness
Constrained Cluster Analysis In-Depth: Analysis of Classifier Effectiveness
Constrained Cluster Analysis In-Depth: Analysis of Classifier Effectiveness
Constrained Cluster Analysis In-Depth: Analysis of Classifier Effectiveness
Constrained Cluster Analysis In-Depth: Analysis of Classifier Effectiveness
Constrained Cluster Analysis In-Depth: Analysis of Classifier Effectiveness
Constrained Cluster Analysis In-Depth: Analysis of Classifier Effectiveness
Constrained Cluster Analysis In-Depth: Analysis of Classifier Effectiveness
Constrained Cluster Analysis Model Selection: Our Risk Minimization Strategy
Constrained Cluster Analysis Recap
Constrained Cluster Analysis References
Kapitel DM:III III. Nearest Neighbor Strategies
Self Organizing Maps Motivation: Räumliche Organisation von Aktivitäten im Gehirn
Self Organizing Maps Idee [Kohonen 1982]
Self Organizing Maps Formales Modell
Remarks:
Self Organizing Maps Formales Modell
Self Organizing Maps Formales Modell
Remarks: Gebräuchlich ist auch die sogenannte Bubble-Neigborhood, die Neuronen innerhalb eines
Self Organizing Maps Algorithmus zur Gewichtsanpassung
Remarks: Die Initialisierung der Gewichte der Neuronen kann mit kleinen Zufallswerten erfolgen.
Self Organizing Maps Algorithmus zur Gewichtsanpassung
Self Organizing Maps Beispiel: Dimensionsreduktion mit SOMs
Self Organizing Maps Beispiel: Dimensionsreduktion mit SOMs
Self Organizing Maps Beispiel: Dimensionsreduktion mit SOMs
Self Organizing Maps Beispiel: Dimensionsreduktion mit SOMs
Self Organizing Maps Beispiel: Spezialfall 2D-SOMs
Self Organizing Maps Beispiel: Spezialfall 2D-SOMs
Self Organizing Maps Beispiel: Spezialfall 2D-SOMs
Self Organizing Maps Anwendungsbeispiel: Traveling Salesman Problem (TSP)
Self Organizing Maps Beispiel: Spezialfall Vektorquantisierung
Neural Gas Motivation
Neural Gas Idee [Martinetz/Schulten 1991]
Neural Gas Formales Modell
Neural Gas Formales Modell
Remarks:
Neural Gas Formales Modell
Neural Gas Formales Modell
Neural Gas Algorithmus zur Gewichts- und Strukturanpassung
Neural Gas Algorithmus zur Gewichtsanpassung
Neural Gas Beispiel: Spezialfall Neuronales Gas in 2D
Kapitel DM:V V. Association Analysis
Assoziationsanalyse Motivation/Überblick
Assoziationsanalyse Spezifikation des Problems der Assoziationsanalyse
Assoziationsanalyse Spezifikation des Problems der Assoziationsanalyse
Assoziationsanalyse k-Itemset, Instanzmenge, Support
Assoziationsanalyse k-Itemset, Support
Kapitel DM:V V. Association Analysis
Frequent Itemset Mining Häufige k-Itemsets
Frequent Itemset Mining Häufige k-Itemsets
Frequent Itemset Mining Häufige k-Itemsets
Frequent Itemset Mining Abgeschlossene häufige Itemsets, Maximal häufige Itemsets
Frequent Itemset Mining Abgeschlossene häufige Itemsets, Maximal häufige Itemsets
Bemerkungen:
Frequent Itemset Mining Abgeschlossene häufige Itemsets, Maximal häufige Itemsets
Frequent Itemset Mining A-Priori Algorithmus
Frequent Itemset Mining A-Priori Algorithmus
Bemerkungen:
Frequent Itemset Mining A-Priori Algorithmus
Bemerkungen:
Frequent Itemset Mining Beispiel: A-Priori Algorithmus mit σmin =
Frequent Itemset Mining Beispiel: A-Priori Algorithmus mit σmin =
Frequent Itemset Mining Effizienzverbesserungen A-Priori Algorithmus
Kapitel DM:V V. Association Analysis
Regel-Mining Von häufigen Itemsets zu Regeln
Regel-Mining Von häufigen Itemsets zu Regeln
Regel-Mining Assoziationsregeln
Regel-Mining Extraktion von Assoziationsregeln
Regel-Mining Extraktion von Assoziationsregeln
Regel-Mining Beispiel: Extraktion von Assoziationsregeln
Regel-Mining Evaluierung von Assoziationsregeln
Regel-Mining Evaluierung von Assoziationsregeln
Regel-Mining Evaluierung von Assoziationsregeln
Regel-Mining Evaluierung von Assoziationsregeln
Regel-Mining Beispiel Lift
Regel-Mining Beispiel Lift
Regel-Mining Zusammenfassung